{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn import datasets\n",
    "\n",
    "\n",
    "from collections import defaultdict\n",
    "\n",
    "# 加载数据集\n",
    "iris_datas = datasets.load_iris()\n",
    "\n",
    "# 设置点的不同形状，不同形状默认颜色不同，也可自定义\n",
    "style_list = ['o', '^', 's']       \n",
    "data = iris_datas.data\n",
    "labels = iris_datas.target_names\n",
    "cc = defaultdict(list)\n",
    "\n",
    "for i, d in enumerate(data):\n",
    "    cc[labels[int(i/50)]].append(d)\n",
    "    pass\n",
    "\n",
    "p_list = []\n",
    "c_list = []\n",
    "\n",
    "for each in [0, 2]:\n",
    "    for i, (c, ds) in enumerate(cc.items()):\n",
    "        draw_data = np.array(ds)\n",
    "        p = plt.plot(draw_data[:, each],\n",
    "                        draw_data[:, each+1], style_list[i])\n",
    "        p_list.append(p)\n",
    "        c_list.append(c)\n",
    "        pass\n",
    "\n",
    "    plt.legend(map(lambda x: x[0], p_list), c_list)\n",
    "    # 鸢尾花的花瓣或花萼的长度和宽度\n",
    "    plt.title('iris petal length and width') if each else plt.title('iris calyx length and width')\n",
    "    plt.xlabel('petal length(cm)') if each else plt.xlabel('calyx width(cm)')\n",
    "    plt.ylabel('petal width(cm)') if each else plt.ylabel('calyx width(cm)')\n",
    "    plt.show()\n",
    "    pass\n",
    "\n",
    "pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x123ba9470>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# plt.style.use('classic')\n",
    "\n",
    "x = np.arange(0, 10, 1)\n",
    "y = np.arange(1, 8, 1)\n",
    "\n",
    "# 画坐标点\n",
    "xv, yv = np.meshgrid(x, y)\n",
    "\n",
    "plt.plot(xv, yv, '.')\n",
    "plt.grid(True)\n",
    "plt.show()\n",
    "\n",
    "z = np.sqrt(xv ** 2 + yv ** 2)\n",
    "plt.imshow(z, cmap=plt.cm.gray)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%pylab inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import axes3d\n",
    "from scipy.stats import multivariate_normal\n",
    "\n",
    "x = np.linspace(-10, 10, 500)\n",
    "y = np.linspace(-10, 10, 500)\n",
    "X, Y = np.meshgrid(x, y)\n",
    "\n",
    "pos = np.empty(X.shape + (2,))\n",
    "pos[:, :, 0] = X\n",
    "pos[:, :, 1] = Y\n",
    "\n",
    "# 均值\n",
    "mean = [0, 0]\n",
    "# 方差\n",
    "cov = [[3, 0], [0, 15]]\n",
    "rv = multivariate_normal(mean=mean, cov=cov)\n",
    "\n",
    "# 3D画图\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(projection='3d')\n",
    "ax.plot_surface(X, Y, rv.pdf(pos), cmap='viridis', linewidth=0)\n",
    "ax.set_xlabel('X axis')\n",
    "ax.set_ylabel('Y axis')\n",
    "ax.set_zlabel('Z axis')\n",
    "# plt.legend(loc='best', title='2D Normal')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
  },
  "kernelspec": {
   "display_name": "Python 3.7.3 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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